CMCLRec: Cross-modal Contrastive Learning for User Cold-start Sequential Recommendation-Reference-Cited by-同舟云学术

CMCLRec: Cross-modal Contrastive Learning for User Cold-start Sequential Recommendation

Published:2024-07-10 Issue: Volume:9 Page:1589-1598
ISSN:
Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Xu Xiaolong¹^ORCID,Dong Hongsheng¹^ORCID,Qi Lianyong²^ORCID,Zhang Xuyun³^ORCID,Xiang Haolong¹^ORCID,Xia Xiaoyu⁴^ORCID,Xu Yanwei⁵^ORCID,Dou Wanchun⁶^ORCID

Affiliation:

1. Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

2. China University of Petroleum (East China), Qingdao, Shandong, China

3. Macquarie University, Sydney, New South Wales, Australia

4. RMIT University, Melbourne, Victoria, Australia

5. Tianjin University, Tianjin, China

6. Nanjing University, Nanjing, Jiangsu, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657839

Reference42 articles.

1. RecSys Challenge 2017

2. Veselka Boeva and Christian Nordahl. 2019. Modeling evolving user behavior via sequential clustering. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 12--20.

3. Generative Adversarial Framework for Cold-Start Item Recommendation

4. A survey on deep learning and its applications

5. Socially-aware Dual Contrastive Learning for Cold-Start Recommendation

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